Maximum Likelihood Estimation in a Mixture Regression Model Using the Continuation Method
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概要
- 論文の詳細を見る
To an extremely difficult problem of finding the maximum likelihood estimates in a specific mixture regression model, a combination of several optimization techniques is found to be useful. These algorithms are the continuation method, Newton-Raphson method, and simplex method. The simplex method searches for an approximate solution in a wider range of the parameter space, then a combination of the continuation method and the Newton-Raphson method finds a more accurate solution. In this paper, this combination method is applied to find the maximum likelihood estimates in a Weibull-power-law type regression model.
- 社団法人電子情報通信学会の論文
- 2003-05-01
著者
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Hirose Hideo
Department Of Applied Physics Faculty Of Engineering Nagoya University
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Hirose Hideo
Department Of Control And Engineering Science Kyushu Institute Of Technology
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KOMORI Yoshio
Department of Control and Engineering Science, Kyushu Institute of Technology
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Komori Yoshio
Department Of Control And Engineering Science Kyushu Institute Of Technology
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